Effective Analysis of Multilayer Perceptron and Sequential Minimal Optimization in Prediction of Dyscalculia among Primary School Children
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science & Engineering | India | Volume 5 Issue 8, August 2016 | Popularity: 7 / 10


     

Effective Analysis of Multilayer Perceptron and Sequential Minimal Optimization in Prediction of Dyscalculia among Primary School Children

Sampada Margaj, Dr. Seema Purohit


Abstract: This study basically focuses on the two classification methods, Multilayer perceptron (MLP) and sequential minimal optimization (SMO), for the prediction of Dyscalculia among primary school children. Prediction of any of the categories of learning disability is not an easy task. Same is the case of dyscalculia. Detail knowledge of the subject is mandatory in accurate prediction of dyscalculia in any child. A sooner the detection faster we can overcome it which will help the child for bright future. Among above mentioned classifiers MLP gives us best accuracy results. This study will also reflect on determining the best classification method for our specific domain.


Keywords: Dyscalculia, MLP, SMO, Classification


Edition: Volume 5 Issue 8, August 2016


Pages: 581 - 585



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Sampada Margaj, Dr. Seema Purohit, "Effective Analysis of Multilayer Perceptron and Sequential Minimal Optimization in Prediction of Dyscalculia among Primary School Children", International Journal of Science and Research (IJSR), Volume 5 Issue 8, August 2016, pp. 581-585, https://www.ijsr.net/getabstract.php?paperid=ART2016861, DOI: https://www.doi.org/10.21275/ART2016861

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